Tupman, CA
How exposed is Tupman to wildfire?
Tupman's 112 buildings earn a 87th-percentile wildfire-risk score nationally under USFS's model — in USFS's highest wildfire-risk band nationally. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Tupman's burn probability — fire likelihood with no building count factored in — sits at the 89th percentile nationally.
Where Tupman's buildings actually sit
65.2% of Tupman's 112 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 34.8% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
Tupman against the rest of the country
Tupman's 87th national percentile looks worse in isolation than its 55th ranking inside California does — this place is on the milder end for its own state, by 32 points. Among the 31,521 US communities USFS scores, Tupman ranks 4,123 for wildfire risk (1 is highest) and 28,532 by building count (1 is largest). Within California alone, it ranks 717 of 1,570 places by risk. See the full county-by-county picture for California on its state page.
What this risk score means for insurance
Tupman sits in California, one of two states that legally require a wildfire-risk disclosure at sale. California's FAIR Plan, the state's insurer of last resort, ended 2025 with 668,609 residential policies after adding 21,859 in Q4 alone — the kind of market shift a 87th-percentile score like Tupman's can end up mattering for. More on the disclosure law.
Lowering exposure, not just insuring around it
Because 65.2% of Tupman's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Tupman's figures come from
The methodology guide shows exactly how USFS turned 112 counted buildings into the percentiles shown above for Tupman. The exposure-zones guide covers what Tupman's dominant indirect exposure actually means, with real examples from across the dataset.